Abstract TMP66: Intravenous Thrombolysis is Associated with Lower Risk of Severe Disability and Death among SPAN-100 Positive Acute Ischemic Stroke Patients
Bibliographic record
Abstract
BACKGROUND: Clinicians are cautious about administering intravenous thrombolysis (tPA) to acute ischemic stroke (AIS) patients who are very elderly and/or have severe neurological deficits. The Stroke Prognostication using Age and NIHSS (SPAN) index combines age plus stroke severity (NIHSS) to create a binary measure (≥ 100 vs. < 100) to predict clinical outcome. We evaluated the effectiveness of tPA by SPAN-100 index status among a large sample of AIS patients. METHODS: Data on 7140 AIS participants in the Virtual International Stroke Trials Archive (VISTA) collaboration. Outcome measures included severe disability or death at 3 months (defined as modified Rankin Scale {mRS} 4-6) and death alone. Effect of tPA on outcomes was assessed using multivariable logistic regression adjusting for SPAN-100 status. RESULTS: Among all patients, 743 (10.5%) were SPAN-100 positive (≥ 100), and 2731 (38.2%) received tPA treatment. Of those treated with tPA, SPAN-100 positive patients were more likely to experience severe disability or death (73.2% vs. 36.3%; p<0.0001) or death alone (33.6% vs. 11.4%; p<0.0001) than SPAN-100 negative patients. However, among SPAN-100 positive patients, tPA was associated with a significantly lower risk of severe disability and death, and tPA had a significantly greater treatment effect among SPAN-100 positive vs. SPAN-100 negative patients (Table). Logistic regression analyses showed significant interactions between SPAN-100 status and tPA (mRS of 4-6 <0.001; death 0.029) confirming that tPA had a greater treatment effect among SPAN-100 positive vs. SPAN-100 negative patients, even after adjustment for age and NIHSS. CONCLUSIONS: Despite the low probability of a favorable outcome, tPA reduces the risk of severe disability and death among SPAN-100 positive AIS patients. SPAN-100 index can be readily used in emergency care settings to identify high risk AIS patients who may be less prone to catastrophic outcomes after tPA treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".